Abstract
This paper explains a potential approach to synthetic data generation using genetic algorithms. It based on the principle that optimisation can be strong, accurate and efficient if there is sufficient prior knowledge of solution space. This approach is applicable because its evolutionary and competitive process compares different synthetic versions of the original data and combines their fitness in the finalised dataset.
Original language | English |
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Title of host publication | Proceedings of the 1st International Workshop on AI for Privacy and Security |
Place of Publication | New York |
Publisher | ACM Digital Library |
Number of pages | 6 |
ISBN (Electronic) | 978-1-4503-4304-6 |
DOIs | |
Publication status | Published - 29 Aug 2016 |
Research Beacons, Institutes and Platforms
- Cathie Marsh Institute